Abstract

Homogeneity or heterogeneity of cells is the most fundamental and important features of analyzing biological associations of genes and gene products. Recent bioinformatics technology requires an automated high-throughput analysis application that can handle massively produced data from next generation sequences and dramatically increased size of public proteomic/genomic databases. Although Gene ontology (GO) database has been newly spotlighted on its wide coverage of machine-readable terminologies, its complex DB schema and vast amount of applications utilizing GO without deep considerations of GO term relations dilute the actual power of GO-based analysis and resulted in misleading/under estimated outcomes. Meanwhile, our recent studies showed that BSM score, a new way of measuring functional similarity, clearly outperformed existing conventional methods. However, implementing BSM score that requires integrating multiple databases and calculating scoring matrix is not trivial and even difficult for bioinformatics experts; therefore, a web-based graphical user interface (GUI) tool, Gene Ontology Analysis Layer (GOAL: \url{http://www.ittc.ku.edu/chenlab/goal}) is introduced to provide user-friendly GO application powered by state of art functional similarity metric, BSM score.